COGNITIVE MODELLING OF AN EFFECTIVE SYSTEM OF INFORMATION SUPPORT OF AGRICULTURAL ENTERPRISES

  • Volodymyr Kharchenko Faculty of Information Technologies, National University of Life and Environmental Sciences of Ukraine https://orcid.org/0000-0001-5067-7181
  • Tetiana Balanovska Faculty of Agricultural Management, National University of Life and Environmental Sciences of Ukraine https://orcid.org/0000-0001-6814-5888
  • Olga Gogulya Faculty of Agricultural Management, National University of Life and Environmental Sciences of Ukraine
  • Hanna Kharchenko Faculty of Agricultural Management, National University of Life and Environmental Sciences of Ukraine https://orcid.org/0000-0002-0705-447X

Abstract

This article encompasses the methodology of cognitive modelling of complex poorly structured systems. Based on the expert method and with the help of this modelling methodology, the main factors that influence the effectiveness of information support of agricultural entrepreneurship were identified and the direction of their action was determined. There has been developed a cognitive map that reflects the cumulative impact of various factors on each other, as well as on the effectiveness of the information system for agricultural entrepreneurship. Hidden patterns between factors influencing the effectiveness of information support of agricultural entrepreneurship are revealed based on the cognitive map. The scenario approach is simulated based on different trends that reflect the current situation. This model allows us to further evaluate the performance of the system of information support of agricultural entrepreneurship under the influence of the environment, to predict its development, as well as to develop optimal strategic decisions that are aimed at ensuring sustainable development.

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Published
2021-04-21
How to Cite
Kharchenko, V., Balanovska, T., Gogulya, O., & Kharchenko, H. (2021). COGNITIVE MODELLING OF AN EFFECTIVE SYSTEM OF INFORMATION SUPPORT OF AGRICULTURAL ENTERPRISES. Proceedings of the International Scientific Conference "Economic Sciences for Agribusiness and Rural Economy", (4). https://doi.org/10.22630/ESARE.2020.4.7